Dynamic Model for Comparing the Performance of …...1 Dynamic Model for Comparing the Performance...

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Dynamic Model for Comparing the Performance of Waste

Management Strategies over Sustainability Dimensions

Diana C. Tascón-Hoyos

Universidad Santo Tomás - Science and Technology Faculty Professor

Universidad Distrital Francisco José de Caldas – Master's degree in Industrial Engineering

Bogotá D.C., Colombia 110221

[email protected]

Abstract

This paper aims to show a System Dynamics model proposed to evaluate and compare

the impact of diverse waste management strategies on Construction and Demolition

(C&D) debris over some environmental, ecological and economic aspects as dimensions

for measuring sustainability. The model looks to promote systematic thinking about

relations between strategic decisions over C&D waste management and its long term

consequences over sustainability and also to provide a model that allows decision makers

to simulate and study the potential impact of several waste strategies; those strategies

were focused on two types, operational and regulative related. The model was run with

some generic data contextualized in Bogotá D.C, Colombia, in order to show the expected

results and behavior and also to provide a guideline for setting up the conclusions that

were reached, those conclusion are concentrated on the methodological approach

followed, instead of the behavior and analysis of the data set used.

Key Words: System Dynamics, Construction and Demolition Waste Management,

Sustainability Performance Indicators.

Introduction

Understanding a strategy as a combination of ways and modes used to achieve the

objectives of a system in the presence of uncertainty (Francés, 2006), the decision makers

in different industries face a wide range of possibilities, each of them with different

impacts over the dimensions and objectives of sustainability within the context in which

those strategies would potentially be implemented.

The System Dynamic Model presented in this paper aims to provide an approach to

evaluate and compare the impact over sustainability dimensions caused by some

operational and regulatory strategies potentially implemented to manage C&D debris.

Firstly there is a brief definition of the problem and its background, after that; it is shown

the way in which the model was conceived and structured, it included the development

of four modules that are Generation and Waste Management, Logistics Strategies,

Regulatory Strategies and a System of Indicators; then a set of scenarios were configured

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and simulated, and finally the conclusions reached as consequence of the design of the

model are presented.

Brief Problem Background

The literature review shows us that some of the existing models of comparison of

strategies on C&D debris management have been made by using Systems Dynamics.

Taking advantage of the approach to represent dynamic and complex systems, this is the

case of Calvo, Varela-Candamio, & Novo-Corti (2014) and Yuan (2012). Other authors

such as Dantana, Touran, & Wang (2004), provide a framework of indicators to evaluate

the performance of C&D industry in terms of its sustainability. Multicriteria analysis was

proposed by Roussat, Dujet, & Méhu (2008). There are also authors focused on the

assessment of specific factors like economic and environmental impact such as Kucukvar,

Egilmez, & Tatari (2014), and Dantana, Touran, & Wang (2004).

Considering the performance measures proposed by the authors studied, it is evident that

in several cases the most relevant sustainability dimension of study is environmental

which is the case of Calvo, Varela-Candamio, & Novo-Corti (2014), Yuan, Chini, & Shen

(2012), Wu & Yu (2014), and Kucukvar, Egilmez, & Tatari (2014).

Dantana, Touran, & Wang (2005) evaluate the economic impact. On the other side Yuan

(2012), propouses a model focused on the social performance. Roussat, Dujet, & Méhu

(2008) designed a system of indicators that contemplate the social, environmental and

economic criteria.

In terms of the strategies to be compared and after considering a significant range of

possibilities on C&D waste management strategies available in literature, it was decided

to include within the framework and scope of the proposed model two generic operational

strategies. Those are:

Conventional demolition, the buildings are demolished without sorting different

components, after the demolition; the waste goes through a selection process in a

collection center. After the classification of the different fractions of waste, the materials

that can be used are reprocessed while there is capacity to do so. The non-usable ones

will be disposed in a landfill as well as those that can be used but exceed the processing

and storage capacity of the collection centers.

Selective demolition, also known as deconstruction, refers to the process of dismantling

buildings in the reverse order from which they were constructed. The removed materials

are stored for reuse or recycling and those that cannot be reused or recycled are discarded.

(Dantana, Touran, & Wang, 2005). C&D waste is classified separating hazardous

components (Roussat, Dujet, & Méhu, 2008).

For the development of the model it was assumed that only reusable C&D waste is

flowing throw the system, leaving out the particular treatment of items like dangerous

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components since those must have a special handling and are not susceptible to being

reused.

In terms of regulatory aspects, studies such as Calvo, Varela-Candamio, & Novo-Corti

(2014), were taken as reference. Those emphasize the implementation of penalties, taxes

and incentives as strategies that allow the Government to influence the behavior of the

sector and thus the C&D waste recovering system. Consequently, penalties, taxes and

incentives are regulatory strategies into the designed model.

Conceptualization and construction of the model

The dynamic model in reference is conceived from a modular perspective, which

contemplates four modules integrated with each other, namely:

Module 1: Generation and management of C&D waste

Module 2: Logistics Strategies

Module 3: Regulatory Strategies

Module 4: Systems of indicators

Figure 1 displays the modular design proposed, the set of indicators offered is related to

sustainability dimensions and it is shown in Table 1.

Figure 1. Modular composition of the dynamic model

Source: Own elaboration

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Table 1. Performance indicators included in the designed model

Sustainability

dimension Indicator Definition of the variable

Nomenclature

/ Units References

Social impact Employment

generation

Estimation of jobs generated

for the management of C&D

waste during the planning

horizon.

𝑆𝑂𝐼𝑥1

[Jobs]

Yuan (2012),

Wu & Yu,

(2014)

Social

perception of

C&D waste

management

Degree of satisfaction of the

population in the perception

of the management of C&D

waste

𝑆𝑂𝐼𝑥2

[%]

Yuan (2012),

Wu & Yu,

(2014)

Environmental

impact

Land use Volume of landfill consumed

by C&D waste, either by

controlled or uncontrolled

disposal

𝐸𝑁𝐼𝑥1

[𝑚3]

Yuan (2012),

Wu & Yu

(2014),

Kucukvar,

Egilmez, &

Tatar (2014)

Pollution of

water sources

Volume of water sources

affected by the C&D waste, it

is associated with the

uncontrolled disposal

𝐸𝑁𝐼𝑥2

[𝑚3]

Yuan (2012),

Wu & Yu,

(2014),

Kucukvar,

Egilmez, &

Tatar (2014)

Economic

impact

Recovery of

economic value

Rate of recovery of economic

value of C&D waste. It is

measured as the equivalent

fraction of C&D materials

that are used in the industry

from C&D waste treatment

activities after discounting

the costs of the related

operations, also considering

them as a fraction of C&D

waste.

𝐸𝐶𝐼𝑥1

[%]

Yuan (2012),

Wu & Yu,

(2014)

Cost of C&D

waste treatment

and recovery

operations

Cost of treatment and

recovery operations carried

out during the planning

horizon.

𝐸𝐶𝐼𝑥2

[$]

Yuan (2012)

Transportation

costs

Transport costs of C&D

wastes generated during the

planning horizon, these

include those addressed to

both the controlled and


𝐸𝐶𝐼𝑥3

[$]

Yuan (2012)


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Module 1: Generation and management of C&D waste

In the research article “A system dynamics model for dynamic capacity planning of

remanufacturing in closed-loop supply chains” by Vlachos, Georgiadis, & Iakovou

(2006), a system dynamics model is proposed, the model aims to establish an optimal

strategy for the planning of remanufacturing capacities in a closed loop Supply Chain

using as optimization criterion the Net Present Value of the total profit during the

planning horizon.

A capacity strategy must take into account a large number of factors, including, but not

limited to, demand patterns, cost of building and operating new facilities, new

technologies and strategies of competitors (Fleischmann, et all 1997). (Fleischmann, Bloemhof-Ruwaard,

Dekker, Van Der Laan, Van Nunen, & L.N., 1997)

Capacity planning is a complex issue, even after deciding to expand capacity, a large

number of expansion alternatives must be considered including where, when, and how

much among other factors under the criterion of the two opposing objectives of capacity

planning, such as maximization of market share and maximization of capacity utilization

(Vlachos, Georgiadis, & Iakovou, 2006).

Given the similarities that the management of C&D debris present with the manufacturing

processes studied by these authors and the relevance of their research, their dynamic

model was taken as a frame of reference for designing the first module; adapting its

variables and feedback loops to the problem and context in which the proposed model

was placed.

According to that, Table 2 contains the denominations of the variables used for the

construction of the first module of the dynamic model (Generation and Management of

C&D waste), together with its definition, type and units for measurement. Figure 2 shows

the causal loop diagram. Figure 3 shows the Forrester diagram proposed for this first

module.

The causal diagrams, level diagrams and simulation presented in the next pages were

made and performed by using Vensim ® PLE by Ventana Systems. Inc. software.

Table 2. Variables included for the Generation and Management of C&D waste module

Notation Definition Type Dimension

𝐶𝐷𝑤 𝐺𝑒𝑛 𝑟𝑡 C&D waste generated per month Rate [kt/month]

𝐶𝐷𝑤 𝐺𝑒𝑛 𝑟𝑡 0 C&D waste generated per month at moment 0 Cte. [kt/month]

𝑟𝑡 𝑑𝑒 𝐼𝑛𝑐 𝐺𝑒𝑛 Percentage increment over C&D waste generated

per month

Cte. [1]

𝐶𝐷𝑤 𝐺𝑒𝑛 𝐴𝑐𝑢𝑚 Total C&D waste generated during the simulation

period

Level [kt]

𝐶𝐷𝑤 𝐿𝑣 Level of C&D waste in system Level [kt]

𝑟𝑡 𝑅𝐶𝐿 C&D waste flow rate in collection and inspection

facilities

Rate [kt/month]

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𝐶𝐷𝑤 𝑅𝐶𝐿 𝑙𝑣0 Initial rate of waste C&D flow to collection and

inspection facilities

Rate [kt/month]

𝐶𝑎𝑝 𝑅𝐶𝐿 Maximum volume of C&D waste that can be

handled by collection facilities per unit of time

Level [kt/month]

𝐶𝑎𝑝 𝑅𝐶𝐿 0 Initial collection capacity Cte. [kt/month]

𝐹𝑎𝑐𝑡 𝐶𝑎𝑝 𝑅𝐶𝐿 0 Factor used to calculate Cap RCL 0. Indicates the

initial fraction of demolished C&D waste that is

legally disposed.

Cte. [1]

𝑟𝑡 𝐼𝑛𝑐 𝐶𝑎𝑝𝑅𝐶𝐿 Rate of increase of collection capacity Rate [kt/month]

𝑂𝑏𝑗 𝐶𝑎𝑝 𝑅𝐶𝐿 Collection Capability Objective Rate [kt/month]

𝐹𝑎𝑐𝑡 𝑂𝑏𝑗 𝐶𝑎𝑝 𝑅𝐶𝐿 Factor used to calculate the 𝑂𝑏𝑗 𝐶𝑎𝑝 𝑅𝐶𝐿 as a

function of 𝐶𝐷𝑤 𝐺𝑒𝑛 𝑟𝑡

Cte. [1]

𝐷𝑖𝑠𝑐𝑟 𝑂𝑏𝑗 𝐶𝑎𝑝 𝑅𝐶𝐿 Discrepancy between 𝑂𝑏𝑗 𝐶𝑎𝑝 𝑅𝐶𝐿 and

𝐶𝑎𝑝 𝑅𝐶𝐿

Aux. [kt/month]

𝐹𝑎𝑐 𝐼𝑛𝑐 𝐶𝑡𝑒 𝐶𝑎𝑝 𝑅𝐶𝐿 Constant increase factor of the𝐶𝑎𝑝 𝑅𝐶𝐿, is

activated when the target, 𝑂𝑏𝑗 𝐶𝑎𝑝 𝑅𝐶𝐿 has not

been reached.

Aux. [1/month]

𝐹𝑎𝑐 𝐴𝑢𝑥 𝐼𝑛𝑐 𝐶𝑎𝑝 𝑅𝐶𝐿 Aux Factor. Of increase of the capacity of

constant collection, originated by factors and

policies external to the variables of the model

Cte. [1/month]

𝐼𝑛𝑐 𝐶𝑎𝑝𝑅𝐶𝐿 𝐷𝑒𝑐𝑡 Increased collection capacity for the

implementation of selective demolition

(deconstruction)

Aux. [kt/month]

𝑟𝑡 𝑑𝑖𝑠𝑝 𝑁𝐶 It is the flow of C&D waste to be disposed of as a

consequence of insufficient collection capacity

(Cap_RCL), or industry players' preference for

doing so

Rate [kt/month]

𝐶𝐷𝑤 𝑑𝑖𝑠𝑝 𝑁𝐶 Level C&D waste arranged in an uncontrolled

manner

Level [kt]

𝑃𝑟𝑒𝑓 𝑁𝐶 𝑅𝑒𝑔 The degree of preference of the companies of the

sector to dispose their C&D waste in an

uncontrolled (illegal) way, is a regulated value

that varies between 0 and 1 corresponding to a

fraction of C&D waste

Aux. [1]

𝑆𝑖𝑛𝑘 1 Disposal rate of C&D waste arranged in an

uncontrolled manner

Rate [kt/month]

𝐶𝐷𝑤 𝑅𝐶𝐿 𝑙𝑣 Level of C&D waste collected Level [kt]

𝐹𝑟 𝐶𝐷𝑤 𝐴𝑐𝑐 Fraction of C&D waste collected accepted to be

reused

Aux. [1]

𝐹𝑟 𝐶𝐷𝑤 𝑅𝑒𝑗 Fraction of C&D waste collected rejected for

reuse

Aux. [1]

𝐶𝐷𝑤 𝑎𝑐𝑐𝑒𝑝𝑡𝑒𝑑 𝑟𝑒𝑢𝑠𝑒 Flow of C&D waste passing inspection and

suitable for reuse

Rate [kt/month]

𝐶𝐷𝑤 𝑟𝑒𝑗𝑒𝑐𝑡𝑒𝑑 𝑟𝑒𝑢𝑠𝑒 Waste C&D flow that does not pass the

inspection and should be discarded

Rate [kt/month]

7


𝐶𝐷𝑤 𝑅𝑒𝑢𝑠𝑎𝑏𝑙𝑒 𝑙𝑣 Level of C&D waste that meets the conditions to

be reprocessed or recycled

Level [kt]

𝑟𝑡 𝑜𝑓 𝑑𝑖𝑠𝑝 𝑆𝐶 C&D recoverable waste surplus inventory flow,

which in order to prevent costly accumulation,

should be discarded if there is not enough

capacity for handling

Rate [kt/month]

𝐶𝐷𝑤 𝑑𝑖𝑠 𝑆𝐶 Level of C&D waste disposed in a controlled way Level [kt]

𝑆𝑖𝑛𝑘 2 Final disposal rate of C&D waste disposed in a

controlled way

Rate [kt/month]

𝐶𝑎𝑝 𝑃𝑅 The maximum volume of C&D waste that can be

reprocessed in the treatment facilities of the

system

Level [kt/month]

𝐹𝑎𝑐𝑡 𝐶𝑎𝑝 𝑃𝑅 0 Factor used to calculate initial processing

capacity as a fraction of the C&D waste demand

in the market

Cte. [1]

𝐹𝑎𝑐𝑡 𝑂𝑏𝑗 𝐶𝑎𝑝 𝑃𝑅 Factor used to calculate the target of processing

capacity as a function of C&D waste demand in

the market

Cte. [1]

𝐷𝑖𝑠𝑐𝑟 𝐶𝑎𝑝 𝑂𝑏𝑗 Discrepancy between Cap PR and its objective Aux. [kt]

𝑃𝑅 𝑟𝑡 Flow of C&D waste treated through recovery

facilities

Rate [kt/month]

𝑟𝑡 𝐼𝑛𝑐 𝐶𝑎𝑝𝑃𝑅 Rate of increase of processing capacity

(recovery)

Rate [kt/month]

𝐹𝑎𝑐 𝐼𝑛𝑐 𝐶𝑎𝑝𝑃𝑅 Factor of increase of the processing capacity, is

used to calculate the 𝑟𝑡 𝐼𝑛𝑐 𝐶𝑎𝑝𝑃𝑅 based on

demand for C&D waste in the market

Aux. [kt]

𝐴𝑢𝑥 𝐼𝑛𝑐 𝐶𝑎𝑝𝑃𝑅 Increase in processing capacity, used to calculate

𝐹𝑎𝑐 𝐼𝑛𝑐 𝐶𝑎𝑝𝑃𝑅 based on C&D waste demand in

the market

Cte. [1]

𝐶𝐷𝑤 𝑃𝑅 𝑀𝑎𝑟𝑘𝑒𝑡 Level of C&D waste processed and available to

be reincorporated into the market

Level [kt]

𝐶𝐷𝑤 𝑃𝑅 𝑈𝑠𝑀𝑎𝑟𝑘𝑒𝑡 Reinstatement rate in the processed C&D waste

market

Rate [kt/month]

𝐴𝑐𝑢𝑚 𝐶𝐷𝑤 𝑃𝑅 𝑈𝑠𝑀𝑎𝑟𝑘𝑒𝑡 C&D waste used in the market accumulated

during the planning horizon

Level [kt]

𝐷𝑒𝑚𝑎𝑛𝑑 𝐶𝐷𝑤 𝑃𝑅 𝑀𝑎𝑟𝑘𝑒𝑡 Demand in the C&D waste treated market Level [kt]

𝑃𝑟𝑒𝑓 𝑑𝑖𝑠 𝑁𝐶 Preference for uncontrolled disposal Level [1]

𝑃𝑟𝑒𝑓 𝑑𝑖𝑠 𝑁𝐶 0 Initial preference for uncontrolled disposal Level [1]

𝑟𝑡 𝐼𝑛𝑐 𝑃𝑟𝑒𝑓 𝑑𝑖𝑠 𝑁𝐶 Rate of increase of preference for uncontrolled

disposal

Rate [1/month]

𝑀𝑎𝑇𝑎𝑥 𝐷𝑖𝑠𝑝 𝑆𝐶 Marginal tax charged for disposal of C&D waste

in landfills. This variable comes from the module

of regulatory strategies

Aux. [$/kt]

8


𝐹𝑎𝑐 𝐼𝑛𝑐 𝑃𝑟𝑒𝑓 𝑁𝐶 𝑇𝑎𝑥 An estimated factor that would increase the

preference for the uncontrolled provision as a

result of taxes for reported C&D waste generation

Aux. [1/$/kt]

[kt/$]

𝐶𝑜𝑠𝑀𝑎𝑇𝑟 𝑁𝐶 Marginal cost of transportation to landfills or

other illegal disposal sites

Aux. [$/kt]

𝐶𝑜𝑠𝑀𝑎𝑇𝑟 𝑆𝐶 Marginal cost of transportation to legal collection

centers

Aux. [$/kt]

𝑅𝑒𝑙 𝐶𝑜𝑠𝑀𝑎𝑇𝑟 𝑁𝐶/𝑆𝐶 Cost Ratio 𝐶𝑜𝑠𝑀𝑎𝑇𝑟 𝑁𝐶/𝐶𝑜𝑠𝑀𝑎𝑇𝑟 𝑆𝐶 Aux. [1]

𝐹𝑎𝑐 𝐼𝑛𝑐 𝑃𝑟𝑒𝑓 𝑁𝐶 𝐶𝑜𝑠 𝑁𝐶/𝑆𝐶

An estimated factor that would increase the

preference for uncontrolled disposal as a

consequence of the differences between transport

costs by controlled and uncontrolled disposal

Aux. [1]

𝑟𝑡 𝑑𝑒𝑐 𝑃𝑟𝑒𝑓 𝑑𝑖𝑠 𝑁𝐶 Rate of decreasing preference for uncontrolled

disposal

Aux. [kt/month]

𝐹𝑎𝑐 𝑑𝑒𝑐 𝑃𝑟𝑒𝑓 𝑁𝐶 𝐶𝑜𝑠 𝑁𝐶/𝑆𝐶

Estimated decreasing factor in preference for

uncontrolled disposal as a consequence of

differences between transportation costs by

controlled and uncontrolled disposal

Aux. [1]

𝐹𝑎𝑐 𝑑𝑒𝑐 𝑃𝑟𝑒𝑓 𝑁𝐶 𝑃𝑒𝑀𝑎 Estimated decreasing factor in preference for

uncontrolled disposal as a consequence of

marginal penalty for illegal disposal

Aux. [1]

𝑃 𝑃𝑒 𝑑𝑖𝑠𝑝 𝑁𝐶 Probability of assigning penalties by uncontrolled

disposal. This variable comes from the module of

regulatory strategies

Aux. [1]

𝑃𝑒𝑀𝑎 𝑑𝑖𝑠𝑝 𝑁𝐶 Marginal penalty for uncontrolled disposal. This

variable comes from the module of regulatory

strategies

Aux. [$/kt]

𝑂𝑏𝑗 𝑃𝑟𝑒𝑓 𝑑𝑖𝑠 𝑁𝐶 Target in preference for uncontrolled provision Aux. [1]

𝐷𝑖𝑠𝑐𝑟 𝑂𝑏𝑗 𝑃𝑟𝑒𝑓 𝑑𝑖𝑠 𝑁𝐶 Discrepancy between preference for uncontrolled

disposal and its target value

Aux. [kt/month]


9

Figure 2. Causal loop diagram for module 1

Own elaboration

CDw disp NC

CDw RCL lvCap RCL

CDw Reusables lv

Cap PR

CDw disp SC

CDw Pr MarketCDw lv

Fr CDw AccFac Inc CapPR

Pref dis NC

Rel CosMaTrNC/SC

Discr Obj Pref

dis NC

Pref NC Reg

Fr CDw Rej

Fac Inc Cte CapRCL

Discr Obj CapRCL

Discr CapObj

CDw Gen rt

Sink 1

CDw rejected

reuse

Sink 2

PR rt

rt Inc CapPR

rt RCL

rt de disp SCrt disp NC

rt Inc Pref dis NC

rt dec Pref dis NC

CDw accpted

reuse

+

-

<CDw Dect>

-

-

<CDw Dem>

+

-

<Inc CapRCLDect>

--

+

+

-+

+

-

++

-

-

+

<Demanda CDw

PR Market>

+

++

+

+

+

CDw PR

UsMarket

+

-

-

+

-

+

+

--

+

+

-

+

<P Pe disp NC>

+

rt Inc CapRCL

+

+-

++

+

+

-

+

+

+

+

+

+

+

+

Acum CDw PR

UsMarket

+

CosMaTr dis SC

-

CosMaTr dis NC

-

10

Figure 3. Forrester diagram for module 1

Own elaboration

CDw disp NC

CDw RCL lv

Cap RCL

CDw Reusables lv

Cap PR

CDw disp SC

CDw Gen Acum

CDw Gen rt rt RCL

rt Inc CapRCL

CDw accepted

reuse

CDw rejected

reuse

CDw Pr Market

rt disp NC

rt de disp SC

PR rt

Sink 1Sink 2

CDw PR

UsMarket

CDw lv

Fr CDw Acc

<Fr CDw Acc>

Cap RCL 0

<Inc CapRCL

Dect>

<CDw Acc Total>

rt Inc CapPR

Fac Inc CapPR

Pref disNC

rt Inc Pref dis NC rt dec Pref dis NC

CosMaTr dis NC CosMaTr dis SC

<P Pe disp NC>

<PeMa disp NC>

Rel CosMaTrNC/SC

Pref dis NC 0

Fac Inc Pref NC

Imp

Fac Inc Pref NC

Cos NC/SC Fac dec Pref NC

Cos NC/SC Fac dec Pref NC

PeMa

Obj Pref dis NC

Discr Obj Pref

dis NC<Discr Obj Pref

dis NC>

Pref NC Reg<Pref dis NC>

<CDw RCL lv> <demand CDw PR

Market>

<TaxMa Gen

CDw>

Fr CDw Rej

Fac Inc Cte CapRCL

Obj Cap RCL

<CDw Gen rt>Fact Obj Cap

RCL

Discr Obj CapRCL

Fac Aux IncCap RCL

Fact CapRCL 0

<CDw Gen rt>

rt de Inc Gen CDw Gen rt 0

<CDw Dect>

<CDw Dem>

<CDw Dect>

CDw RCL lv0

Acum CDw PR UsMarket

<Aux rt [ut]>

<Aux rt [ut]>

<Aux rt [ut]>

<Aux rt [ut]>

<Aux rt [ut]>

Fact Cap PR 0

Fact Obj CapPR

Aux Inc CapPR<demand CDw PR

Market>

Discr CapObj

<Aux rt [ut]>

11

Module 2: Logistics strategies

According to what was exposed before, the scope of the model considers the evaluation of

two types of logistic strategies:

Conventional Demolition (Classification in collection center)

Selective Demolition (Deconstruction)

In order to incorporate the logistic strategies within the model, and their expected impact

over the systems variables shown in Table 3 were included.

Table 3 Variables include for logistics strategies module


𝐹𝑟 𝐶𝐷𝑤 𝐷𝑒𝑐𝑡 Fraction of C&D waste to be deconstructed Cte. [1]

𝐹𝑟 𝐶𝐷𝑤 𝐷𝑒𝑐𝑡 0 Initial fraction of C&D waste to be deconstructed Cte. [1]

𝐹𝑟 𝐶𝐷𝑤 𝐷𝑒𝑚 Fraction of C&D waste to be conventionally

demolished Cte. [1]

𝐹𝑟 𝐶𝐷𝑤 𝐷𝑒𝑚 0 Initial fraction of C&D waste to be conventionally

demolished Cte. [1]

𝑟𝑡 𝐼𝑛𝑐 𝐶𝐷𝑤 𝐷𝑒𝑐𝑡 Rate of increase of fraction of C&D waste to be

deconstructed Cte. [1]

𝐺𝑟𝑎𝑑 𝐼𝑛𝑐 𝐶𝐷𝑤 𝐷𝑒𝑐𝑡 Degree of constant increase over the rate of

deconstruction Cte. [1/month]

𝑂𝑏𝑗 𝐹𝑟 𝐶𝐷𝑤 𝐷𝑒𝑐𝑡 Objective fraction of C&D waste to be deconstructed Cte. [1/month]

𝐷𝑖𝑠𝑐𝑟 𝑂𝑏𝑗 𝐹𝑟 𝐶𝐷𝑤 𝐷𝑒𝑐𝑡 Discrepancy between 𝐹𝑟 𝐶𝐷𝑤 𝐷𝑒𝑐𝑡 and

𝑂𝑏𝑗 𝐹𝑟 𝑅𝐶𝐷 𝐷𝑒𝑐𝑡

Aux. [1/month]

𝐴𝑢𝑥 𝑟𝑡 [𝑢𝑡] Auxiliary variable used to convert by equivalence rates

to units of 1 / month Aux. [1/month]

𝐼𝑛𝑐 𝐶𝑎𝑝𝑅𝐶𝐿 𝐷𝑒𝑐𝑡 Increase in the collection rate expected by the

implementation of deconstruction strategy Aux. [kt/month]

𝐶𝑡𝑒𝐼𝑛𝑐 𝑟𝑡𝑅𝐶𝐿𝐷𝑒𝑐𝑡 Constant increase in collected CDw to be deconstructed Cte. [1]

𝑟𝑡 𝐷𝑒𝑐 𝑅𝐶𝐷 𝐷𝑒𝑚 Decrease of C&D waste demolished Cte. [1/𝑚𝑒𝑠2]

𝐶𝐷𝑤 𝐷𝑒𝑐𝑡 C&D waste coming from deconstruction Aux. [kt/month]

𝐶𝐷𝑤𝐷𝑒𝑚 C&D waste coming from demolition Aux. [kt/month]

𝐶𝐷𝑤𝐷𝑒𝑐𝑡 𝑅𝐶𝐿 C&D waste from deconstruction collected Aux. [kt/month]

𝐶𝐷𝑤 𝐷𝑒𝑚 𝑅𝐶𝐿 C&D waste from demolition collected Aux. [kt/month]

𝐹𝑟 𝐴𝑐𝑐 𝐷𝑒𝑐𝑡 Fraction of C&D waste from deconstruction that is

accepted for treatment Cte. [1]

𝐹𝑟 𝐴𝑐𝑐 𝐷𝑒𝑚 Fraction of C&D waste from demolition that is

accepted for treatment Cte. [1]

𝐶𝐷𝑤 𝐷𝑒𝑐𝑡 𝐴𝑐𝑐 C&D waste from deconstruction accepted for treatment Aux. [kt/month]

𝐶𝐷𝑤 𝐷𝑒𝑚 𝐴𝑐𝑐 C&D waste from demolition accepted for treatment Aux. [kt/month]

%𝐼𝑛𝑐 𝐶𝑜𝑠𝑡𝑜 𝑂𝑝𝑒𝑟 𝐷𝑒𝑐𝑡 Constant percentage of increase of operating costs for

moving from conventional demolition to deconstruction Cte. [1]

12


𝐼𝑛𝑐 𝐶𝑜𝑠𝑡 𝑂𝑝𝑒𝑟 𝐶𝐷𝑤 𝐷𝑒𝑐𝑡 Percent increase in operating costs for moving from

conventional demolition to deconstruction Aux. [1]

Source: own elaboration

A logistics strategy would be configured by defining the variables shown in Table 4

Table 4. Variables that make up a logistics strategy

Variable Description

𝑂𝑏𝑗 𝐹𝑟 𝑅𝐶𝐷 𝐷𝑒𝑐𝑡 Objective fraction of C&D waste to

deconstruct

𝐺𝑟𝑎𝑑 𝐼𝑛𝑐 𝑑𝑒 𝑅𝐶𝐷 𝐷𝑒𝑐𝑡 Degree of constant increase that brings the

deconstruction rate


Figure 4 shows the causal diagram and Figure 5 the Forrester diagram for module 2, this is

focused on the decision of how much of the C&D waste generated in the system should be

deconstructed, and how fast that transition, form demolition to deconstruction is expected to

be.


Own elaboration

Fr CDw Dect

Fr CDw Dem

Fr Acc Dect Fr Acc Dem

Inc CapRCLDect

CteInc rtRCLDect

CDw DemCDw Dect

<CDw lv>

CDw Dect Acc CDw Dem Acc

CDw Acc Total

<Discr Obj CapRCL>

Inc Cost Oper

CDw Dect

%Inc CostoOper Dect

<Fr CDw Dem>

Obj Fr CDw Dect

Discr Obj Fr

CDw Dect

Grad Inc de CDw

Dect

CDw Dem RCLCDw Dect RCL

<Cap RCL>

rt Inc CDw Dec rt Dec CDw Dem

+ +

+

+

+

-

+

+

+ +

+ +

+

+ +

++

--

+

+

-

+

+-

+

+

13


Own elaboration

Fr CDw Dect Fr CDw Dem

Fr Acc Dect Fr Acc Dem

Inc CapRCLDect

CteInc rtRCLDect

<CDw lv>

CDw DemCDw Dect

<CDw lv>

CDw Dect Acc CDw Dem Acc

CDw Acc Total

<Discr Obj CapRCL>

Inc Cost Oper

CDw Dect

%Inc CostoOper Dect

<Fr CDw Dem>

<Fr CDw Dect>

Obj Fr CDwDect

Discr Obj Fr

CDw Dect

rt Inc CDw Dect

Fr CDw Dect 0

Grad Inc deCDw Dect

rt Dec CDw Dem

Fr CDw Dem 0

<rt Inc CDw

Dect>

<rt dispNC>

CDw Dem RCLCDw Dect RCL

<Cap RCL><Cap RCL>

Aux rt [ut]

14

Module 3: Regulatory Strategies

According to Karavezris (2007), cited by Yuan (2012), governments play a crucial role in

promoting C&D waste management practices through the strengthening of industry-wide

regulations, in various regions such as Shenzhen, China, Governmental regulations have been

identified as the most important factor driving the management of C&D waste, Lu & Yuan

(2010).

The search for economic efficiency through the inclusion of external costs in the productive

system has generated different environmental policy instruments (Rodríguez Camargo,

2008), those are classified as legal instruments (environmental conditioning or standards)

and market economy oriented instruments (emission taxes, emissions certificates, offsets), a

third classification consisted of the combination of those instruments (emissions trading).

As for the case of logistic strategies, the regulatory strategies to be studied were basically

delimited to:

Penalty policies aiming to promote 3R actions (reduce, reuse and recycle), in the

management of waste C&D or environmental taxes with tax penalties that increase

collection (ER1)

Incentive or regulatory policies aimed at promoting 3R or incentive taxes created to

change the behavior of producers and / or consumers (ER2)

To incorporate the impact of regulatory strategies within the system, variables shown in

Table 5 were included.

Table 5. Variables included for the regulatory strategies module


𝐸𝑅 1 Degree in which the regulatory strategy

is implemented 1, Three levels are

proposed for the model (High: 1,

Medium: 1/3: Null: 0)

Cte. [1]

𝐸𝑅 2 Degree in which regulatory strategy is

implemented 2, Three levels are

proposed for the model (High: 1,

Medium: 1/3: Null: 0)

Cte. [1]

𝐶𝑜𝑠 𝑃𝑒 𝑑𝑖𝑠𝑝 𝑁𝐶 𝑁𝑣 Level of penalties paid for uncontrolled

provision accumulated during the

planning horizon

Level [$]

15


𝐼𝑚𝑝 𝑅𝐶𝐷 𝑔𝑒𝑛 𝑁𝑣 Level of taxes paid by C&D waste

generation accumulated during the

planning horizon

Level [$]

𝑃𝑒 𝐸𝑥𝑐𝐿𝑖𝑚𝑅𝐶𝐿 Level of penalties paid for exceeding

the acceptable limits of cumulative

disposal during the planning horizon

Level [$]

𝑇𝑠 𝐴𝑐𝑢𝑚 𝐶𝑜𝑠 𝑃𝑒 𝑑𝑖𝑠 𝑁𝐶 Rate of accumulation of penalty costs

by uncontrolled disposal

Rate [$/month]

𝑇𝑠 𝐴𝑐𝑢𝑚 𝐼𝑚𝑝 Rate of accumulation of cost of taxes

by generation of C&D waste

Rate [$/month]

𝑇𝑠 𝐴𝑐𝑢𝑚 𝑃𝑒 𝐸𝑥𝑐 𝐿𝑖𝑚𝑅𝐶𝐿 Rate of accumulation of cost of

penalties for exceeding acceptable

limits of disposal

Rate [$/month]

𝐶𝑜𝑠𝑡𝑜 𝑃𝑒 𝑑𝑖𝑠𝑝 𝑁𝐶 Costs of penalty by uncontrolled

provision

Aux. [$/month]

𝑃𝑒𝑀𝑎 𝐷𝑖𝑠𝑝 𝑁𝐶 Marginal penalties for uncontrolled

disposal

Aux. [$/kt]

𝑃 𝑃𝑒 𝑑𝑖𝑠𝑝 𝑁𝐶 Probability of assigning penalties for

uncontrolled (unlawful)

𝑃𝑒𝑀𝑎 𝑁𝐶 𝑠𝑚𝑚𝑙𝑣 Random variable that defines the

marginal cost of penalty by

uncontrolled

Aux. [1/kt]

𝑂𝑝𝑒𝑟 𝐶𝑜𝑛𝑡𝑟𝑜𝑙 𝑑𝑁𝐶 Control operations carried out to find

illegal disposal of C&D waste

Level [operativo]

𝑂𝑝𝑒𝑟 𝐶𝑜𝑛𝑡𝑟𝑜𝑙 𝑑𝑁𝐶0 Control operations carried out at the

initial moment to find illegal disposal

of C&D waste

Cte. [operativo]

𝑇𝑠 𝐼𝑛𝑐 𝑂𝑝𝑒𝑟 𝐶𝑜𝑛𝑡𝑟𝑜𝑙 Rate of increase of realization of

control operations

Rates [operativo/mes]

𝑇𝑠 𝑅𝑒𝑖𝑛𝑣 𝑂𝑝𝑒𝑟 𝐶𝑜𝑛𝑡𝑟𝑜𝑙 Rate of investment of the payment of

penalties that is invested in increasing

the number of operations per month

Aux. [operativo/mes]

𝑂𝑝𝐸𝑟/𝑠𝑚𝑚𝑙𝑣 Factor in which the control operations

increase for each smmlv (Minimum

monthly salary) that is paid through

penalty for illegal disposal

Cte. [1]

𝑠𝑚𝑚𝑙𝑣 Minimum Monthly Legal Salary

Effective in Colombia for 2017, in

millions of COP

Cte. [$]

16


𝐹𝑎𝑐 𝑃 𝑃𝑒 𝑂𝑝𝐶𝑜𝑛 Factor in which the probability of

assigning penalties to Non-Controlled

provisions increase for each control

operation performed

Cte. [1/operative]

𝑀𝑎𝑇𝑎𝑥 𝐺𝑒𝑛 𝑅𝐶𝐷 Marginal tax for C&D waste Aux. [$/kt]

𝐹𝑎𝑐 𝑀𝑎𝑇𝑎𝑥 Factor used to calculate the

𝐼𝑚𝑝𝑀𝑎 𝐺𝑒𝑛 𝑅𝐶𝐷 consistent with the

degree of implementation of the

regulatory strategy ER 1

Cte. [$/kt]

𝐿𝑖𝑚𝑅𝐶𝐿 Acceptance limit accepted by

regulation

Cte. [kt/month]

𝑃𝑒𝑀𝑎 𝑒𝑥𝑐 𝐿𝑖𝑚𝑅𝐶𝐿 Marginal penalty for exceeding the

acceptance limit established by

regulation established for ER1

Aux. [kt/month]

𝐹𝑎𝑐 𝑃𝑒𝑀𝑎 𝐿𝑖𝑚𝑅𝐶𝐿 Factor used to calculate

𝑃𝑒𝑀𝑎 𝑒𝑥𝑐 𝐿𝑖𝑚𝑅𝐶𝐿 consistent with the

degree of implementation of the

regulatory strategy ER1

Cte. [$/kt]

𝐼𝑛𝑐𝑒𝑛𝑀𝑎 Marginal incentive for the use of

treated C&D waste

Aux. [1]

𝐹𝑎𝑐𝐼𝑛𝑐𝑒𝑛𝑀𝑎 Marginal incentive factor for the use of

C&D waste used to calculate the

IncenMa depending on the degree of

ER2 implementation

Cte. [1]

𝐼𝑛𝑀𝑎 𝐼𝑛𝑐 𝑇𝑠 𝑈𝑠 𝑅𝐶𝐷 𝑃𝑅 Percentage of IncenMa evaluated as a

function of the discrepancy between

the use of waste C&D treated in the

market and its target value

Aux. [1]

%𝑂𝑏𝑗 𝑈𝑠 𝑅𝐶𝐷 𝑃𝑟 Percentage of consumption of

processed C&D waste in relation to the

generated C&D waste

Cte. [1]

𝑂𝑏𝑗 𝑈𝑠 𝑅𝐶𝐷 𝑃𝑟 𝑀𝑑𝑜 Net consumption target of C&D waste

processed against C&D waste

generated

Aux. [kt/month]

𝐷𝑖𝑠𝑐𝑟 𝑈𝑠𝑀𝑑𝑜 𝑂𝑏𝑗 % Discrepancy between the use of waste

C&D treated in the market and its

target value

Aux. [1]

𝐼𝑛𝑐 𝑇𝑠 𝑈𝑠 𝑅𝐶𝐷𝑅𝑃 𝐸𝑅2 Increase in the rate of use of C&D

waste treated in the market as a

consequence of the incentives provided

by ER2

Aux. [kt/month]

17


𝐹𝑎𝑐 𝑈𝑠𝑀𝑖𝑛 𝑅𝐶𝐷 𝑃𝑅 Percentage of minimum use of

reprocessed C&D waste in the market

Cte. [1]

𝑇𝑠 𝐼𝑛𝑐 𝑈𝑠𝑀𝑑𝑜 Rate of increase of consumption of

waste C&D treated in the market

Aux. [kt/month]

𝐼𝑛𝑐 𝑇𝑠 𝑈𝑠 𝑅𝐶𝐷𝑅𝑃 𝑂𝐹 Increase in the rate of use of C&D

waste treated in the market as of other

factors

Aux. [kt/month]

𝐹𝑎𝑐 𝐼𝑛𝑐 𝑇𝑠 𝐼𝑛𝑐 𝑈𝑠 𝑅𝐶𝐷 𝑃𝑟 𝑂𝐹 Factor of increase in waste C&D

consumption treated by market

conditions external to regulatory

strategies

Cte. [1]

𝐷𝑒𝑚𝑎𝑛𝑑𝑎 𝑅𝐶𝐷 𝑃𝑅 𝑀𝑑𝑜 Demand for processed C&D waste

treated

Level [kt]

𝐷𝑒𝑚𝑎𝑛𝑑𝑎 𝑅𝐶𝐷 𝑃𝑅 𝑀𝑑𝑜 0 Initial demand for processed C&D

waste

Cte. [kt]


Penalty policies are expected to affect mainly the rate of uncontrolled disposal, as there are

fines associated with the illegal dumping of waste.

Law 1333 of 2009 in Colombia establishes the environmental sanction procedure; it defines

penalties to those responsible for environmental infractions that include fines of 5000 smmlv,

closure of establishments, and even demolition at the expense of the offender (Congreso de

la República de Colombia, 2009). The uncontrolled provision refers specifically to the

unlawful disposal, so the evaluation of penalty strategies would be directly related to this

rate. Figure 7 shows the Forrester diagram conceived for the inclusion of this module into

the model.

A regulatory strategy would be configured by defining the variables shown in Table 7.

Table 6. Variables that make up a regulatory strategy

Variable Description

𝐸𝑅 1

Implemented degree of regulatory strategy 1: Taxes / Penalties

𝐸𝑅 2 Implemented degree of regulatory strategy 2: Incentives


18


Own elaboration

ER 1

ER 2

PeMa disp NC

P Pe disp NCOper Control dNC

Fac P PeOpCon

InMa Inc rt Us

CDw PR

Obj Us CDw Pr

Market

Fac Inc rt Inc Us

CDw Pr OF

Inc rt Us CDwPR

ER2

Inc rt Us

CDwPR OF

Discr UsMarket

Obj %

IncenMa

Costo Pe dispNC

%Obj Us CDw Pr

smmlv

PeMa NCsmmlv

Cos Pe disp NC lv

rt Reilv Oper

Control

OpEr/smmlv

Demanda CDw PR MarketTaxMa Gen CDw

PeMa excLimRCL

LimRCL

Fac MaTax

Fac PeMaLimRCL

Tax CDw gen lv

Pe ExcLimRCL

FacIncenMa

Fac UsMin

CDw PR

<CDw PrMarket>

rt Inc Oper

Control

rt Acum Cos Pe

dis NC

rt Acum Tax

rt Inc UsMarket

rt Acum Pe Exc

LimRCL

+

+

+

+

+

-

+

+

<CDw PR

UsMarket>

-

+

<rt disp NC>

+

+

+

+ +

+

+

+

+

+

+

+

+

+

+

-

+

+

+

+

+

+

-

+

+

+

+

+

19


Own elaboration

ER 1

ER 2PeMa disp NC

P Pe disp NC

Oper Control dNC

Fac P PeOpCon

InMa Inc rt Us

CDw PR

Obj Us CDw Pr

Market

<CDw PR

UsMarket>

Fac Inc rt Inc Us

CDw Pr OF

Inc rt Us CDwPR

ER2

Inc rt Us

CDwPR OF

Discr UsMarket

Obj %

IncenMa<rt disp

NC>

Costo Pe dispNC

%Obj Us CDw Pr

<CDw Genrt>

smmlv

PeMa NCsmmlv

Cos Pe disp NC lv

rt Acum Cos Pe

dis NC

<Costo Pe dispNC>

rt Reilv Oper

Control

<smmlv>OpEr/smmlv

Oper ContdNC0

<P Pe dispNC>

rt Inc Oper

Control

<CDw PrMarket>

demand CDw PR Market

rt Inc UsMarket

demand CDw PR

Market 0

TaxMa Gen CDw

PeMa excLimRCL

LimRCL

Fac TaxMa

Fac PeMaLimRCL

Tax CDw gen lv

<rt RCL>

rt Acum Tax

Pe ExcLimRCL

rt Acum Pe Exc

LimRCL

FacIncenMa

<Discr UsMarket

Obj %>

Fac UsMin

CDw PR

<CDw PrMarket>

Aux [kt] <Aux rt [ut]>

<Aux rt [ut]>

20

Module 4: System of indicators

The development System of indicators module is based on several authors. In particular the

studies of Yuan, H., Chini, A., Lu, Y., Shen, L. (2012), Calvo, Varela-Candamio, & Novo-

Corti (2014), and Yuan (2012), were taken as framework. The indicators included in the

model were previously shown in Table 1.

The articulation of these indicators with the central module of generation and management

of waste C&D gives rise to new variables, interrelations and causal loops. Those variables

are presented in Table 7, while the Forrester diagram associated with the module is shown in

Figure 9.

Table 7. Variables included for the system of indicators module


𝑆𝑂𝐼𝑥1 Estimation of jobs generated for the management

and management of waste C&D during the

planning horizon (simulated period)

Aux. [jobs]

𝑆𝑂𝐼𝑥2 Degree of satisfaction of the population in terms of

the perception of the management of waste C&D in

the City

Aux. [%]

𝐸𝑁𝐼𝑥1 Volume of landfill consumed by disposal of C&D

waste, either by controlled or uncontrolled disposal

Aux. [𝑚3]

𝐸𝑁𝐼𝑥2 Volume of water sources affected by the disposal of

C&D waste, is associated with the uncontrolled

disposal

Aux. [𝑚3]

𝐸𝐶𝐼𝑥1 Economic recovery of C&D waste. It is measured

as the equivalent fraction of C&D materials that are

used in the industry from waste C&D treatment

activities after discounting the costs of the related

operations, also considering them as a fraction of

C&D waste.

Aux. [%]

𝐸𝐶𝐼𝑥2 Cost of treatment and recovery operations carried

out during the planning horizon. It consists of

demolition costs and deconstruction costs

considered in a generic way

Aux. [$]

𝐸𝐶𝐼𝑥3 Cost of transportation of waste C&D generated

during the planning horizon, these include those

addressed to both the controlled and uncontrolled

disposal

Aux. [$]

𝐸𝑚𝑝 𝑅𝐶𝐷 𝑅𝐶𝐿 Jobs generated to handle the controlled collection

of C&D waste

Cte. [jobs/kt]

𝐸𝑚𝑝 𝑅𝐷𝐶 𝑃𝑅 Jobs generated to handle the processing capacity

available in the system

Cte. [jobs/kt]

𝐸𝑚𝑝 𝑂𝑝𝑟 𝐷𝑒𝑐𝑡 𝐷𝑒𝑚 Jobs generated by demolition and deconstruction

activities

Aux. [jobs]

𝐸𝑚𝑝𝑀𝑎 𝐶𝑎𝑝 𝑅𝐶𝐿 Jobs generated per unit of C&D waste collected Cte. [jobs/kt]

21


𝐸𝑚𝑝𝑀𝑎 𝐶𝑎𝑝 𝑃𝑅 Jobs generated for per unit of processed C&D waste Cte. [jobs/kt]

𝐸𝑚𝑝𝑀𝑎 𝑂𝑝𝑟 𝐷𝑒𝑐𝑡 Jobs generated per unit of C&D waste

conventionally demolished

Cte. [jobs/kt]

𝐸𝑚𝑝𝑀𝑎 𝑂𝑝𝑟 𝐷𝑒𝑚 Jobs generated per C&D waste unit deconstructed Cte. [jobs/kt]

𝑣𝑣 𝑑𝑖𝑠𝑝 𝑆𝐶 Volume of landfill used per C&D waste unit in its

controlled disposal

Aux. [𝑚3]

𝑣𝑡 𝑑𝑖𝑠𝑝 𝑁𝐶 Volume of land used per C&D waste unit in its


Aux. [𝑚3]

𝐹𝑟 𝑅𝐶𝐷 𝑑𝑖𝑠𝑝 𝑁𝐶 𝐹𝐻 Fraction of water sources affected by uncontrolled

disposal per waste C&D unit

Cte. [1]

𝐹𝑎𝑐 𝑅𝑒𝑐𝐸𝐶 𝑃𝑅 Recovery factor of C&D waste by equivalence with

recovery of economic value per kt processed with

exit to the market

Cte. [1]


Figure 8. Causal diagram for module 4

Own elaboration

ECIx1 ECIx2

ECIx3

ENIx1

ENIx2

SOIx1

SOIx2

<Cap PR> <CDw dispSC>

<CDw dispNC>

Emp RDC PR

Emp CDw RCL

<Cap RCL>

Fr CDw disp

NC FH

vv disp SC vt disp NC

<Fr CDw disp

NC FH>

EmpMa CapPR

EmpMa CapRCL

Fac RecEC PR

Emp Opr Dect

Dem

EmpMa Opr Dect

<Fr CDw Dect>

<Fr CDw Dem>

EmpMa Opr Dem

<CDw lv>

<Inc Cost Oper

CDw Dect>

<CDw disp NC>

<CDw disp SC>

++

+

+

+

+

++

++

+

--

-

-

-

-

-<PR rt>

<rt disp NC>

+

-

+

+ +

<CosMaTr

dis NC><CDw disp SC>

<CosMaTr dis

SC>

++ +

+

22


Own elaboration

Simulated scenarios

The first of the simulated strategies consists of a scenario in which a 33% degree of

implementation of taxes and penalties policy is fixed, which leads to relatively low values in

those aspects. The strategy of deconstructing is privileged by setting up its target value in

80% and its gradual implementation rate at 5% per month. No incentives were considered.

The second of the simulated strategies consists of a scenario in which a degree of 100%

implementation of tax and penalties policy is established. Deconstruction strategy is fixed in

ECIx1 ECIx2

ECIx3

ENIx1

ENIx2

SOIx1

SOIx2

<Cap PR>

<rt dispNC>

<PR rt>

<CDw dispSC>

<CDw dispNC>

Emp CDw PR

Emp CDw RCL

<Cap RCL>

Fr CDwdisp NC HS

vv disp SC vt disp NC

<Fr CDwdisp NC HS>

EmpMa CapPR

EmpMa CapRCL

Fac RecEC PR

Emp Opr DectDem

EmpMa Opr Dect

<Fr CDw Dect>

<Fr CDw Dem>

EmpMa Opr Dem

<CDw lv>

<Inc Cost OperCDw Dect>

<CosMaTrdis SC>

<CosMaTrdis NC>

<CDw disp NC>

<CDw disp SC>

<Acum CDwPR UsMarket>

<Aux rt [ut]>

<TIMESTEP>

<TIMESTEP>

<TIMESTEP>

23

a low value of 20% and its gradual implementation rate at 5% per month. No incentives were

considered.

The third one consists of a scenario with a 33% degree implementation of taxes and penalties.

Deconstruct strategy is set up in a medium value of 50% and its gradual implementation rate

at of 2.5% monthly. Incentives were set up at a degree of 100% of their maximum values

stablished.

The results obtained after running a 60 month length simulation of this scenarios are shown

in the graphs included in Tables 8, 9 and 10.

Table 8. Comparative graphs of simulated scenarios, environmental performance

Own elaboration

Table 9. Comparative graphs of simulated scenarios, social performance

Own elaboration

24

Table 10. Comparative graphs of simulated scenarios, economic performance

Own elaboration

Conclusions

The dynamic model for contrasting management strategies of Construction and Demolition

Waste was proposed articulating four modules interrelated with each other, one of the

modules integrates the system of indicators to contrast the performance of the strategies to

be evaluated.

The review of the literature allowed us to identify that there is an interest to provide different

performance management frameworks for waste management, with special emphasis on one

or more of the component dimensions of sustainability. They are presented from different

disciplines or approaches and were an essential input for the integration of the proposed

model.

Within the strategies studied for waste management, it is possible to speak of two broad

categories, some of which include logistical or operational aspects conceived within the

industry and its component links and others of an external nature, which are usually

established by Governments, such as regulation and normative, that includes incentive

25

strategies or penalties for the results of waste management in the construction and demolition

sector.

Since the impact of construction and demolition waste management is likely to be categorized

in the environmental, economic and social areas, it was possible to define a system of

indicators that would include indexes specific to each of these. Integrative indicators for each

dimension were proposed to evaluate the strategies in terms of its sustainability performance.

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